NDLI: Experiments in malay information retrieval

Content Provider	IEEE Xplore Digital Library
Author	Sembok, T.M.T. Bakar, Z.A. Ahmad, F.
Copyright Year	2011
Description	Author affiliation: Faculty of Information Science and Technology, The National University of Malaysia, Bangi, 43600, Malaysia (Sembok, T.M.T.) \|\| Faculty of Mathematical and Computer Sciences, Universiti Technologi MARA, Shah Alam, 43600, Malaysia (Bakar, Z.A.) \|\| Faculty of Science and Technology, National Defence University of Malaysia, Kem Sungai Besi, 57000, Malaysia (Ahmad, F.)
Abstract	There have been very few studies on the use of conflation algorithms for indexing and retrieval of Malay documents. The two main classes of conflation algorithms are string-similarity algorithms and stemming algorithms. Stemming is used in information retrieval systems to reduce variant word forms to common roots in order to improve retrieval effectiveness. As in other languages, there is a need for an effective stemming algorithm for the indexing and retrieval of Malay documents. Again there are few research on n-gram string-similarity measures done on Malay. We have experimented on the application of stemming and string similarity matching on retrieving of verses from the Al-Quran in order to evaluated their effectiveness. Before retrieval effectiveness can be carried out an experimental data set need to be developed which comprises of a collection of documents, a set of queries, and their relevant judgements. In this paper we will describe the development of the experimental data set and the application of stemming and similarity matching algorithms in retrieving the verses from the Al-Quran. Inherent characteristics of n-grams and several variations of experiments performed on the queries and documents are discussed. The variations are: both non-stemmed queries and documents; stemmed queries and nonstemmed documents; and both stemmed queries and documents. Further experiment are then carried out by removing the most frequently occurring n-gram. The dice-coefficient is used as threshold and weight in ranking the retrieved documents. Beside using dice coefficients to rank documents, inverse document frequency weights are also used. Interpolation technique and standard recall-precision functions are used to evaluate the retrieval effectiveness.
Starting Page	1
Ending Page	5
File Size	562878
Page Count	5
File Format	PDF
ISBN	9781457707537
ISSN	21556830
e-ISBN	9781457707520
DOI	10.1109/ICEEI.2011.6021578
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-17
Publisher Place	Indonesia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Information science Natural languages Natural Language Processing Information retrieval Educational institutions n-gram Classification algorithms Information Retrieval Indexes Stemming
Content Type	Text
Resource Type	Article

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